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Wasserstein distributional adversarial training for deep neural networks

Wasserstein distributional adversarial training for deep neural networks

13 February 2025
Xingjian Bai
Guangyi He
Yifan Jiang
Jan Obloj
    OOD
ArXivPDFHTML

Papers citing "Wasserstein distributional adversarial training for deep neural networks"

12 / 12 papers shown
Title
Robustness and Accuracy Could Be Reconcilable by (Proper) Definition
Robustness and Accuracy Could Be Reconcilable by (Proper) Definition
Tianyu Pang
Min Lin
Xiao Yang
Junyi Zhu
Shuicheng Yan
61
121
0
21 Feb 2022
RobustBench: a standardized adversarial robustness benchmark
RobustBench: a standardized adversarial robustness benchmark
Francesco Croce
Maksym Andriushchenko
Vikash Sehwag
Edoardo Debenedetti
Nicolas Flammarion
M. Chiang
Prateek Mittal
Matthias Hein
VLM
277
689
0
19 Oct 2020
Uncovering the Limits of Adversarial Training against Norm-Bounded
  Adversarial Examples
Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples
Sven Gowal
Chongli Qin
J. Uesato
Timothy A. Mann
Pushmeet Kohli
AAML
39
328
0
07 Oct 2020
Reliable evaluation of adversarial robustness with an ensemble of
  diverse parameter-free attacks
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks
Francesco Croce
Matthias Hein
AAML
192
1,821
0
03 Mar 2020
Transfusion: Understanding Transfer Learning for Medical Imaging
Transfusion: Understanding Transfer Learning for Medical Imaging
M. Raghu
Chiyuan Zhang
Jon M. Kleinberg
Samy Bengio
MedIm
55
980
0
14 Feb 2019
Generalizing to Unseen Domains via Adversarial Data Augmentation
Generalizing to Unseen Domains via Adversarial Data Augmentation
Riccardo Volpi
Hongseok Namkoong
Ozan Sener
John C. Duchi
Vittorio Murino
Silvio Savarese
OOD
100
777
0
30 May 2018
Do Better ImageNet Models Transfer Better?
Do Better ImageNet Models Transfer Better?
Simon Kornblith
Jonathon Shlens
Quoc V. Le
OOD
MLT
136
1,319
0
23 May 2018
Evasion Attacks against Machine Learning at Test Time
Evasion Attacks against Machine Learning at Test Time
Battista Biggio
Igino Corona
Davide Maiorca
B. Nelson
Nedim Srndic
Pavel Laskov
Giorgio Giacinto
Fabio Roli
AAML
101
2,142
0
21 Aug 2017
Adversarial Discriminative Domain Adaptation
Adversarial Discriminative Domain Adaptation
Eric Tzeng
Judy Hoffman
Kate Saenko
Trevor Darrell
GAN
OOD
203
4,646
0
17 Feb 2017
Towards Evaluating the Robustness of Neural Networks
Towards Evaluating the Robustness of Neural Networks
Nicholas Carlini
D. Wagner
OOD
AAML
168
8,513
0
16 Aug 2016
Learning without Forgetting
Learning without Forgetting
Zhizhong Li
Derek Hoiem
CLL
OOD
SSL
241
4,357
0
29 Jun 2016
How transferable are features in deep neural networks?
How transferable are features in deep neural networks?
J. Yosinski
Jeff Clune
Yoshua Bengio
Hod Lipson
OOD
145
8,309
0
06 Nov 2014
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